Search results for "Sentiment Analysis"

Are customer star ratings and sentiments aligned? A deep learning study of the customer service experience in tourism destinations

2023

AbstractThis study explores the consistency between star ratings and sentiments expressed in online reviews and how they relate to the different components of the customer experience. We combine deep learning applied to natural language processing, machine learning and artificial neural networks to identify how the positive and negative components of 20,954 online reviews posted on TripAdvisor about tourism attractions in Venice impact on their overall polarity and star ratings. Our findings showed that sentiment valence is aligned with star ratings. A cancel-out effect operates between the positive and negative sentiments linked to the service experience dimensions in mixed-neutral reviews.

2020

Peer review is often criticized for being flawed, subjective and biased, but research into peer review has been hindered by a lack of access to peer review reports. Here we report the results of a study in which text-analysis software was used to determine the linguistic characteristics of 472,449 peer review reports. A range of characteristics (including analytical tone, authenticity, clout, three measures of sentiment, and morality) were studied as a function of reviewer recommendation, area of research, type of peer review and reviewer gender. We found that reviewer recommendation had the biggest impact on the linguistic characteristics of reports, and that area of research, type of peer…

A Layered Architecture for Sentiment Classification of Products Reviews in Italian Language

2017

The paper illustrates a system for the automatic classification of the sentiment orientation expressed into reviews written in Italian language. A proper stratification of linguistic resources is adopted in order to solve the lacking of an opinion lexicon specifically suited for the Italian language. Experiments show that the proposed system can be applied to a wide range of domains.

When a new technological product launching fails: A multi-method approach of facial recognition and E-WOM sentiment analysis

2018

Abstract The dual aim of this research is, firstly, to analyze the physiological and unconscious emotional response of consumers to a new technological product and, secondly, link this emotional response to consumer conscious verbal reports of positive and negative product perceptions. In order to do this, biometrics and self-reported measures of emotional response are combined. On the one hand, a neuromarketing experiment based on the facial recognition of emotions of 10 subjects, when physical attributes and economic information of a technological product are exposed, shows the prevalence of the ambivalent emotion of surprise. On the other hand, a nethnographic qualitative approach of sen…

Prediction of User-Brand Associations Based on Sentiment Analysis

2023

Finding the right users to be chosen as targets for advertising campaigns is not a trivial task, and it may allow important commercial advantages. A novel approach is presented here for the recommendation of new possible consumers to brands interested in distributing advertising campaigns, ranked according to the “compatibility” between users and brands. A database containing both descriptions associated with different brands, and textual information about users' opinions on different topics, is required in input. Then, sentiment analysis techniques are applied to measure to what extent the users match with the brands, based on the texts associated with their opinions. The approach has been…

Analysis and Comparison of Deep Learning Networks for Supporting Sentiment Mining in Text Corpora

2020

In this paper, we tackle the problem of the irony and sarcasm detection for the Italian language to contribute to the enrichment of the sentiment analysis field. We analyze and compare five deep-learning systems. Results show the high suitability of such systems to face the problem by achieving 93% of F1-Score in the best case. Furthermore, we briefly analyze the model architectures in order to choose the best compromise between performances and complexity.

Sentiment Analysis of Twitter in Tourism Destinations

2020

[EN] Given the importance of electronic word of mouth (eWOM), this paper analyses the content of messages generated by users related to a tourist destination and shared through Twitter. We propose three research questions regarding eWOM behaviour in Twitter focused on the expertise of the reviewer, sentiment analysis of a tweet and its content.In order to address those research questions we carry out text mining analysis by retrieving existing information on Twitter (over 1500 tweets) regarding to Venice as a tourist destination.

Cognitive Reasoning and Inferences through Psychologically based Personalised Modelling of Emotions Using Associative Classifiers

2014

The development of Microsoft Kinect opened up the research field of computational emotions to a wide range of applications, such as learning environments, which are excellent candidates to trial computational emotions based algorithms but were never feasible for given consumer technologies. Whilst Kinect is accessible and affordable technology it comes with its' own additional challenges such as the limited number of extracted Action Units (AUs). This paper presents a new approach that attempts at finding patterns of interaction between AUs and each other on one hand and patterns that link the related AUs to a given emotion. In doing so, this paper presents the ground work necessary to reac…

A Novel Approach for Supporting Italian Satire Detection Through Deep Learning

2021

Satire is a way of criticizing people (or ideas) by ridiculing them on political, social, and morals topics often used to denounce political and societal problems, leveraging comedic devices such as parody exaggeration, incongruity, etc.etera. Detecting satire is one of the most challenging computational linguistics tasks, natural language processing, and social multimedia sentiment analysis. In particular, as satirical texts include figurative communication for expressing ideas/opinions concerning people, sentiment analysis systems may be negatively affected; therefore, satire should be adequately addressed to avoid such systems’ performance degradation. This paper tackles automatic satire…

Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019

2021

Vaccine hesitancy was one of the ten major threats to global health in 2019, according to the World Health Organisation. Nowadays, social media has an important role in the spread of information, misinformation, and disinformation about vaccines. Monitoring vaccine-related conversations on social media could help us to identify the factors that contribute to vaccine confidence in each historical period and geographical area. We used a hybrid approach to perform an opinion-mining analysis on 1,499,227 vaccine-related tweets published on Twitter from 1st June 2011 to 30th April 2019. Our algorithm classified 69.36% of the tweets as neutral, 21.78% as positive, and 8.86% as negative. The perce…